31 Reasons To Reject The Jab

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IgG4 acts as a form of “shepherd” for chronic exposure to things that should not always be pathogens. you get irritated by cat dander and your body responds with histamines and inflammation. but binding by something like like IgG4 would attenuate or even stop that response.

IgG4 is not about removing a pathogen, it’s about creating a “tolerance” by preventing your body from attacking whatever it has bound to. this may be fine for peanuts, but for a replicating respiratory pathogen with high organ affinity, it could be an all access arson pass to burn you down while you fail to elicit any effective immune response.

leaky (non-sterilizing) vaccines are exceedingly dangerous. there is a reason we don’t use them. viruses that can still replicate and spread get forced toward variants that take advantage of the vaccine and its having locked you into one, narrow response vector. and if they can find variants that elicit no IgG3 and lots of IgG4, they get to run riot.

and if you have created a widespread homogeneous herd immunity profile that can be taken advantage of, you’re really in for it.

everybody gets this and no one can generate sound immunity.

this would be entirely unprecedented in human history.

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a better breakdown

🔬 The first study was published in Science Immunology on December 22nd, titled “Class switch towards non-inflammatory IgG isotypes after repeated SARS-CoV-2 mRNA vaccination.” We’ll call this the “December study.” Basically, it ominously suggests that vaccinated people may be developing a systemic tolerance for toxic spike protein.1

The first principle is that there are different KINDS of antibodies, which are used by the human body to handle different kinds of threats. This is similar to how we use different types of military: local police, Border Patrol, Navy, Marines, Army, and so on. The antibodies have shorthand names, like IgA, IgD, IgM, IgE, and IgG. That last one, IgG, has four subtypes, numbered IgG1 through IgG4.

With me so far? Here’s a chart showing the normal, desired immune response to a respiratory virus, by antibody type:

Screenshot from 2022-12-28 16-08-22.png

The left side shows how active each of the antibody types were, which is called “neutralizing effect,” because the antibodies “neutralize” the virus. You’ll see two antibody types doing most of the work: IgM (37.5%) and IgG3 (42.%).

On the right side of the chart, you see the amount (volume) of antibodies found in the serum. Interestingly, IgM (8%) and IgG3 (3%) are only present in small amounts by volume, yet as we can see from the left side, are still doing most of the work neutralizing the virus.

The unsurprising takeaway is: The TYPE of antibody is way more important than how much antibody there is. In this case, the body needs the IgM’s and IgG3’s to neutralize respiratory viruses.

IgM is like the Marines, which come in first to defeat the rebel army. IgG is more like well-armed local police, who stay behind to keep the peace after the territory has been occupied.

One reason IgM is the type that defeats the virus is that, unlike IgG, it is produced in the mucus membranes, where respiratory viruses flourish. We’ve learned that the covid jabs do NOT spur production of IgM, which is one big reason why they failed to stop the transmission and why breakthrough infections occur.

That the jabs spur IgG but don’t increase IgM means the IgG type has to do work it wasn’t designed for in people who’ve never been infected. It’s like sending beat cops to fight the rebel army. They can win, given enough of them, but it’s not the best strategy.

Still, you fight with the army you have, not the army you wish you had. The trouble is, not just ANY type of IgG will work; the body needs neutralizing IgG3. And this is where the jab locomotives really start flying off the rails.

You’d think the FDA would’ve made Pfizer measure IgM and IgG3 antibody levels, and not just general antibody levels. You’d think a lot of things, like unicorns, and like pots of gold at the end of rainbows. But it’s not just that they measured the wrong antibodies. The new studies appear to show that repeated jabs are somehow SUPPRESSING IgG3 antibodies, forcing the body to try to compensate with types not designed for respiratory viruses.
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Two studies1,2 from Israel, posted as preprints on 16 July, find that two doses of the vaccine made by pharmaceutical company Pfizer, based in New York City, and biotechnology company BioNTech, based in Mainz, Germany, are 81% effective at preventing SARS-CoV-2 infections. And vaccinated people who do get infected are up to 78% less likely to spread the virus to household members than are unvaccinated people. Overall, this adds up to very high protection against transmission, say researchers.
so wrong

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💉 The top of the Wall Street Journal’s opinion section this morning finally asks the obvious question: “Are Vaccines Fueling New Covid Variants?”

A New England Journal of Medicine study published last month provides more evidence of the vulnerability caused by immune imprinting. Neutralizing antibodies of people who had received the bivalent were 26 times as high against the original Wuhan variant as they were against XBB and four times as high as they were against Omicron and the BA.5 variant.​

What this shows is that jabbed people are uselessly mounting much stronger responses to the original Wuhan variant than they are against the new variants, which is strong evidence that their immune systems have been “imprinted” with the archaic version of the virus. Then the article cited the even newer Cell study finding much worse performance by jabbed people against XBB:

Similarly, a study this month in the journal Cell found that antibody levels of people who had received four shots were 145 times as high against the original Wuhan strain as the XBB variant. A bivalent booster only slightly increased antibodies against XBB. Experts nevertheless claim that boosters improve protection against XBB. That’s disinformation, to use their favored term.​

Another way to say it is jabbed people’s immune response to XBB is 1/145th as good as their response to the now-defunct original Wuhan strain, and the super-duper, new-and-improved “bivalent booster” doesn’t really improve much on that poor performance. It’s so weird how people aren’t sprinting to the pharmacy to get their bivalent boosters.

Back in 2020, some epidemiologists — quoted regularly and often in Coffee & Covid — were warning that mass-use of a “non-sterilizing” vaccine would quickly lead to antibody-evading variants. Apparently this phenomenon has been known to “science” for years, but has been ignored by experts until now. Now that it’s too late.

All this highlights the primary factual difference between coronaviruses and other viruses like measles and polio against which vaccines have staying power. The latter viruses are genetically stable and don’t evolve much. But coronaviruses — including the common cold — are well-known to rapidly evolve, making the prospect of a developing an effective vaccine a never-ending wild goose chase.


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First, the Truth

After all the lockdowns, quarantines, job-losses, masks, and mandates we can now say that for non-elderly, the flu is deadlier than COVID. IFR (Infection Fatality Rate) is calculated by ration of deaths into TOTAL infections. The great John Ioannidis gave us his latest on Covid and I compare it to the flu with CDC data.

Influenza IFR (CDC data):

  • 0–17: 0.005%
  • 0–64: 0.029%
COVID-19 IFR (Ioannidis):

  • 0–19: 0.0003%
  • 0–59: 0.026%
Despite what the media and Team Apocalypse tells you - the pandemic is over. U.S. COVID-19 deaths by week shown below - 2022 is the bottom line of the chart (through Nov 2022).


This is based on the CDC Case Surveillance File. The date is the “earliest date” on record which means 1) the date of the onset of illness; 2) the date of the positive C19 specimen; and/or 3) reported date… the date the CDC received the entry. This is not the DATE of death - but probably off by no more than 30 days.

Here are the numbers by month for cases and deaths.


As we’ve noted in these pages before - these numbers are probably off.


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LOS ANGELES (Reuters) - Sage Stallone, the son of actor Sylvester Stallone, died of a heart attack and a toxicology report showed no signs of excessive drug use, an official with the Los Angeles County Coroner said on Thursday.

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In the Moderna trial, the excess risk of serious AESIs (15.1 per 10,000 participants) was higher than the risk reduction for COVID-19 hospitalization relative to the placebo group (6.4 per 10,000 participants). [3] In the Pfizer trial, the excess risk of serious AESIs (10.1 per 10,000) was higher than the risk reduction for COVID-19 hospitalization relative to the placebo group (2.3 per 10,000 participants).​

In other words, the data showed that Moderna lowered the chance of covid hospitalization by -6.4 per 10,000, but INCREASED the risk of a serious adverse event by +15.1 per 10,000. Therefore, vaccinees’ net risk of a bad outcome increased by +8.7 per 10,000 by taking the Moderna shot.

Pfizer was nearly the same. The data showed Pfizer lowered the chance of covid hospitalization by -2.3 per 10,000, but INCREASED the risk of a serious adverse event by +10.1 per 10,000. Therefore, vaccinees’ net risk of a bad outcome increased by +7.8 per 10,000 by taking the Pfizer shot.

The difference between the two shots makes sense. Moderna contains a much higher dose of mRNA. So the higher risk reduction and higher adverse events in Moderna seems correlated with the amount of mRNA in the shot, just as you would expect.

So, there’s THAT. But now think about what the numbers MEAN for people’s risk of injury. For Pfizer, in their own trial, during just the first four months of the trial, meaning only about two months post-jab, 10.1 folks per 10,000 had a serious adverse event. That’s 1 injury per 1,000 shots, a crazy-high level of injury. Moderna was even worse. At 15.1 injuries per 10,000, it translated to about 1 serious injury in only 662 jabbed.

The study’s drafters were clear about their conclusion that the jabs weren’t SAFE due to excess injuries over the placebo, and that the jabs weren’t EFFECTIVE because they didn’t prevent hospitalization when compared to a placebo (from all causes). While they didn’t exactly beat the drum about it, they didn’t exactly hide their conclusion, either:

Rational policy formation should consider potential harms alongside potential benefits. To illustrate this need in the present context, we conducted a simple harm-benefit comparison using the trial data comparing excess risk of serious AESI against reductions in COVID-19 hospitalization. We found excess risk of serious AESIs to exceed the reduction in COVID-19 hospitalizations in both Pfizer and Moderna trials.​

the numbers

the article